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Increasing flexibility and productivity in Industry 4.0 production networks with autonomous mobile robots and smart intralogistics

Author

Listed:
  • Giuseppe Fragapane

    (Norwegian University of Science and Technology)

  • Dmitry Ivanov

    (Berlin School of Economics and Law)

  • Mirco Peron

    (Norwegian University of Science and Technology)

  • Fabio Sgarbossa

    (Norwegian University of Science and Technology)

  • Jan Ola Strandhagen

    (Norwegian University of Science and Technology)

Abstract

Manufacturing flexibility improves a firm’s ability to react in timely manner to customer demands and to increase production system productivity without incurring excessive costs and expending an excessive amount of resources. The emerging technologies in the Industry 4.0 era, such as cloud operations or industrial Artificial Intelligence, allow for new flexible production systems. We develop and test an analytical model for a throughput analysis and use it to reveal the conditions under which the autonomous mobile robots (AMR)-based flexible production networks are more advantageous as compared to the traditional production lines. Using a circular loop among workstations and inter-operational buffers, our model allows congestion to be avoided by utilizing multiple crosses and analyzing both the flow and the load/unload phases. The sensitivity analysis shows that the cost of the AMRs and the number of shifts are the key factors in improving flexibility and productivity. The outcomes of this research promote a deeper understanding of the role of AMRs in Industry 4.0-based production networks and can be utilized by production planners to determine optimal configurations and the associated performance impact of the AMR-based production networks in as compared to the traditionally balanced lines. This study supports the decision-makers in how the AMR in production systems in process industry can improve manufacturing performance in terms of productivity, flexibility, and costs.

Suggested Citation

  • Giuseppe Fragapane & Dmitry Ivanov & Mirco Peron & Fabio Sgarbossa & Jan Ola Strandhagen, 2022. "Increasing flexibility and productivity in Industry 4.0 production networks with autonomous mobile robots and smart intralogistics," Annals of Operations Research, Springer, vol. 308(1), pages 125-143, January.
    • Handle: RePEc:spr:annopr:v:308:y:2022:i:1:d:10.1007_s10479-020-03526-7
    DOI: 10.1007/s10479-020-03526-7
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    References listed on IDEAS

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    Cited by:

    1. Onifade, Moshood & Adebisi, John Adetunji & Shivute, Amtenge Penda & Genc, Bekir, 2023. "Challenges and applications of digital technology in the mineral industry," Resources Policy, Elsevier, vol. 85(PB).
    2. Nwaila, Glen T. & Frimmel, Hartwig E. & Zhang, Steven E. & Bourdeau, Julie E. & Tolmay, Leon C.K. & Durrheim, Raymond J. & Ghorbani, Yousef, 2022. "The minerals industry in the era of digital transition: An energy-efficient and environmentally conscious approach," Resources Policy, Elsevier, vol. 78(C).
    3. Dabić, Marina & Maley, Jane F. & Črešnar, Rok & Nedelko, Zlatko, 2023. "Unappreciated channel of manufacturing productivity under industry 4.0: Leadership values and capabilities," Journal of Business Research, Elsevier, vol. 162(C).
    4. Tsan-Ming Choi & Alexandre Dolgui & Dmitry Ivanov & Erwin Pesch, 2022. "OR and analytics for digital, resilient, and sustainable manufacturing 4.0," Annals of Operations Research, Springer, vol. 310(1), pages 1-6, March.
    5. Abderahman Rejeb & Andrea Appolloni, 2022. "The Nexus of Industry 4.0 and Circular Procurement: A Systematic Literature Review and Research Agenda," Sustainability, MDPI, vol. 14(23), pages 1-21, November.

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